Robotic Process Automation: A few things to know before you proceed

To grow their competitive advantage, businesses are now looking to invest in a set of digital technologies which will help them automate repetitive and monotonous tasks and instead focus on their core competencies. Therefore, an area of consideration for them is Robotic process automation (RPA). With intelligent software systems, RPA can help businesses to free up their resources for more strategic initiatives.

In 2018 and the years to come, we will see more and more organizations implementing RPA and RPA solutions will possibly be used in more ways and across more processes than they are being used today. According to Gartner forecast, the Robotic Process Automation software market is poised to grow by 41 per cent year over year to 2020.

But, it is important for the IT decision makers to have a clear understanding of the areas where RPA can be implemented and the objective they want to achieve with it. It is also important to understand how it can help them in streamlining existing processes and add value to the customers. We spoke to Raja Raman, Vice President, Sapient Global Markets to know what organizations need to take a close look at before deploying any RPA solution.

What are the things that businesses should keep in mind before any RPA solution deployment?

The first thing to start with is the goals with which business wants to target an RPA solution- Is it to reduce costs, improve operational efficiency, improving accuracy of work done, scaling work to meet growing business needs or something else? What metrics can be used to measure the success of the initiative?

The second step would be to start with the right set of process candidates. Organizations should have a clear prioritization strategy for picking the right candidate. For example – a job that’s unique in nature, only done by a single individual, may not be a useful candidate for RPA. Instead, a work that’s done by a hundred people is a much better candidate – as automation investment is one-time, and the results can be a hundred times over. Similarly, a job that can’t easily be codified into an algorithm and has a lot of manual/discretionary/subjective steps – won’t be a good candidate for RPA compared to a job that’s highly objective and can be codified.

The third step would be to have an adoption strategy in mind. In how many phases will we build this solution? What risks does it bring operationally and what’s the ‘plan B’ in case there’s a failure in RPA on production? How can I leverage people, whose tasks are being automated?

Furthermore, it’s important to build IT capability within the organization as well to sustain RPA investment in long-run, that will feed into decisions like which tool to pick for automation and what consulting firm to hire for contracting out work.

It is often said that cost is no longer the primary driver for RPA adoption? What’s driving RPA then?

RPA targets both cost-efficiency and accuracy of operations. The logical extension to this is IPA (Intelligent Process Automation) that not only automates operations and performs them accurately but is able to leverage AI techniques to look at the data being processed and come up with workflow improvements (“learning”) on its own. So the solutions are moving up the value chain more towards intelligent solutions that can replace not just mechanical aspects but also bring intelligence to the table, just like humans do.

Which processes can be transformed through RPA?

Processes that are rule-based, which can be documented, are great candidates for RPA. Processes, where human discretion is heavily used, aren’t great candidates for RPA. For example, you may have a loan processing operation where every loan request is examined for credit scores, current bank account details, income tax details and some other objective bits of data, and spits out a “yes/no” answer for whether this applicant’s loan is approved. This is easy to code as it is rule-based and is an RPA candidate. On the other hand – take the process of looking at the student applications to universities. The student writes an essay talking about their vision. There are many reference letters and quality of those references (their background, the nature of nomination etc.) is all subjective. In such cases – RPA can at best play an initial filter role, beyond that – the process has to be manual.

Will intelligent automation replace RPA in the long run?

Replacing is not the right word, ‘augmenting’ is more appropriate. RPA has still a long way to go as there are umpteen jobs which are mechanical today and can be automated. Intelligent Process Automation(IPA) takes this journey to next step and as AI tools get more mature, it’ll be increasingly a part of RPA projects.